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Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a Python script named train.py in a local folder named scripts. The script trains a regression model by using scikit-learn. The script includes code to load a training data file which is also located in the scripts folder. You must run the script as an Azure ML experiment on a compute cluster named aml-compute. You need to configure the run to ensure that the environment includes the required packages for model training. You have instantiated a variable named aml-compute that references the target compute cluster. Solution: Run the following code: Does the solution meet the goal?
Yes
No

No

Explanation
The scikit-learn estimator provides a simple way of launching a scikit-learn training job on a compute target. It
is implemented through the SKLearn class, which can be used to support single-node CPU training.
Example:
from azureml.train.sklearn import SKLearn
}
estimator = SKLearn(source_directory=project_folder,
compute_target=compute_target,
entry_script='train_iris.py'
)
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-scikit-learn

You create a classification model with a dataset that contains 100 samples with Class A and 10,000 samples with Class B The variation of Class B is very high. You need to resolve imbalances. Which method should you use?
Partition and Sample
Cluster Centroids
Tomek links

You create an Azure Machine Learning workspace and set up a development environment. You plan to train a
deep neural network (DNN) by using the Tensorflow framework and by using estimators to submit training
scripts.
You must optimize computation speed for training runs.
You need to choose the appropriate estimator to use as well as the appropriate training compute target
configuration.
Which values should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

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